Face recognition is a popular and competitive area of technology. However, the realtime identification of faces of live broadcasts poses an enormous challenge. For such a system to work, a massive support system which has faces of every person (e.g., celebrities, sports stars, etc.) that can possibly appear on television must be created. Yet a system of this scale that is fast and provides high precision is very difficult to achieve. Moreover, taking a considerably smaller subset of people that appear in broadcasts can still result in millions of faces typically seen in broadcasts, but which is a number that cannot be processed in realtime. Furthermore, many celebrity faces look so similar that the required processing for distinguishing such faces in realtime is impractical. The speed at which the results need to be obtained, memory resources required, and low precision are reasons why the realtime identification of faces of live broadcasts at a large scale poses an enormous challenge.